Modern Patrol Strategies: The Benefits of Technology


Patrolling is one of the basic activities performed by law enforcement professionals that have proved to be effective. Patrolling reduces crime rates, which is specifically critical in low-income communities. Some of the most urgent challenges related to patrolling include the lack of manpower and the development of routes for patrol units. Modern patrolling addresses these issues with the help of technology that enhances associated operations.

Artificial intelligence, diverse types of software, drones, and even robots, as well as social media, are turning into common instruments in the law enforcement system. At that, although these tools improve patrolling considerably, their utilization is still associated with certain limitations, such as the need for investment, technological issues, and the lack of training for the personnel. Clearly, these challenges are being addressed, and the existing instruments are constantly being upgraded. Therefore, modern patrol strategies are diverse and effective in achieving multiple goals and solving various issues.


Patrolling has been one of the effective methods to ensure public order and people’s safety. Dewinter et al. (2020) claim that modern law enforcement agencies now pay much attention to the association between crime and place, which has been one of the central topics in current research. Police patrolling can be referred to as “the act of walking or traveling around an area, at regular intervals, in order to protect or supervise it” (as cited in Chen et al., 2017, p. 19).

It has been acknowledged that diverse areas, especially hotspots, require regular patrolling, which reduces crime rates and has a positive influence on the development of communities. Different methods and strategies have been employed to patrol American streets. Police officers walking in certain areas or using diverse types of transportation are still a part of this effort. At that, technology is penetrating this sphere, and such technologies as smart GPS-based systems, robots, and drones are widely utilized to patrol. This paper includes an analysis of current patrol strategies with a focus on the use of technology in this sphere.

Major Challenges Police Have to Face

Prior to the discussion of the recent advances in patrolling, it is important to identify the most burning issues law enforcement specialists encounter. The lack of resources is a lasting and serious issue yet to be addressed. Many departments have no sufficient funds to invest in modernization or purchase the most recent instruments (software, hardware, devices, and others). Insufficient manpower is often associated with the inability of the police to react in a timely manner (Haas & Ferreira, 2017).

On the one hand, police officers are unable to cover the necessary territories and even all the hotspots. The situation is becoming rather alarming in low-income communities of big cities where population is growing at a high pace. On the other hand, officers often need to address immediate issues and situations, which prevents them from following the designed routes. The lack of people is the fundamental problem that leads to other issues.

For example, planning routes is one of the most burning problems to be solved. Numerous methodologies to develop patrolling routes have been created and implemented (Sampaio et al., 2017). Coverage and regularity have been the primary characteristics to consider when planning routes. Dewinter et al. (2020) argue that the major focus is on the so-called hotspots, which is quite logical and leads to favorable outcomes. Hotspots are areas where crime rate is higher compared to other places, which is often estimated with the help of the historical analysis. However, other areas with a low crime rate and population density also need attention and the use of efficient routing strategies. Regularity is the measure that requires the utilization of a specific approach that implies the examination of the optimal intensity of patrolling.

The dosage of patrolling is another important aspect to take into account when creating patrol routes. The number of police officers in a patrol unit depends on the availability of resources and the peculiarities of the patrolled area (Dewinter et al., 2020). It is also important to ensure proper scrutiny and unpredictable patterns (Leigh et al., 2017). Clearly, if police officers patrol the same areas, criminals will be free to commit crimes without the risk of being caught. At present, police utilize various digital tools to build the routes and evaluate their effectiveness. Routing is one of the central topics for the current research on patrolling, and numerous technological advances start playing a key role in the process.


Tracking has been mainly associated with the use of GPS (Global Positioning System) and has become a breakthrough in law enforcement, in general, and patrolling, in particular. One of the most common uses of this advance is the measurement of patrol dosage (Hutt et al., 2021). GPS devices are placed in police officers’ radio sets, and the movement of the personnel is tracked effectively. The data is sent to data centers, where it is analyzed and employed to develop patrolling routes or respond to different situations accordingly.

At that, the use of this technology is still comparatively low due to the novelty of the instrument and the lack of resources. This method is also associated with other limitations that are linked to micro-hotspot patrolling (Hutt et al., 2021). The frequency of the signal sending by GPS is quite low for such areas, and the exact position of the staff can be hard to identify. These gaps can potentially lead to serious issues and pose diverse threats to the personnel. Nevertheless, this technology and similar advances are being developed and improved at a high pace, so law enforcement professionals are willing to continue using these (and similar) instruments in their daily practice.

Route Development

The development of patrol routes is a complex process that encompasses the analysis of multiple aspects. Decades ago, historical analysis was implemented, and diverse algorithms based on it were created manually to identify and cover the so-called hotspots and conduct effective patrolling routes (Leigh et al., 2017). In some places and cases, this model is still employed. Nevertheless, modern police tend to utilize software (such as artificial intelligence) to create patterns and benchmarks, as well as particular routes, improving the overall quality of patrolling.

Numerous studies have been conducted to identify the most successful approaches and models to developing patrol routes. Chen et al. (2017) note that such measures as efficiency, scalability, unpredictability, flexibility, and robustness are critical for the development of effective routes. The researchers analyzed current methodologies and introduced their own online Bayesian Ant-based Patrolling Strategy (BAPS) (Chen et al., 2017).

This model is a comprehensive online tool that addresses the major aspects of patrolling with a focus on collaboration between law enforcement professionals (see Figure 1). The researchers note that their framework is an effective alternative to the widely used Christofides Cyclic Patrolling Strategy (CCPS) that is used as a benchmark. It is also noted that future research should aim at the introduction of methods to coordinate the activity of vehicle patrol and foot patrol. GPS tracking is seen as an important technology facilitating the development of such advances.

Patrolling strategies (a) BAPS and (b) CCPS.
Figure 1. Patrolling strategies (a) BAPS and (b) CCPS.

Numerous other paradigms and models have been developed and implemented. For instance, Haas and Ferreira (2017) proposed an interdiction patrol route tool based on the Stackelberg game that aims at improving hotspot patrolling route development. It is noteworthy that the two instruments mentioned above, as well as the majority of utilized routing methods, are computer-based. Another model is based on a combination of the Bayesian methods and ant colony algorithms (Leigh et al., 2017). The patrolled paths are marked by “virtual pheromone with an exponential decay” (Leigh et al., 2017, p. 404). The level of the pheromone at a certain period of time defines the hotspots that have to be visited, which prevents excessive patrolling of some areas and the allocation of resources in a more efficient manner.

Police officers utilize digital tools that create routes and evaluate their efficiency. Leigh et al. (2017) offered a framework that can address one of the common gaps in the patrol route algorithms. This imperfection is associated with the limited effectiveness of many current routing methods for multiple patrols. In many cases, patrol routes are developed for one police officer, but these strategies are rather inefficient due to the use of a considerable number of resources. Leigh et al. (2017) claim that their algorithms can satisfy the need for the development of routes for many patrols. Combinations of different methods are also utilized, which is instrumental in identifying the most appropriate models in particular settings.

One of the distinctive features of modern routing strategies is the focus on collaboration. This aspect is ingrained in the existing models that are computer-based (Sampaio et al., 2017). Various technological tools (mobile devices facilitating communication and tracking) have become instrumental in creating effective patrol routes. Collaboration among machines, humans, as well as interactions between humans and machines, is becoming more effective due to the utilization of numerous tools. Police officers can share data in a timely manner, which helps in shaping routes in the real-time setting, which is specifically critical in emergency response cases. This aspect has gained momentum recently as it is critical in making decisions immediately and use resources efficiently.

Some of the limitations of the use of digital-based routing methods are related to the lack of resources, rapidly changing conditions, technology-associated gaps. It is necessary to note that routing is only one of many tools employed by law enforcement professionals and cannot be regarded as a cure-all solution (Sampaio et al., 2017). The creation of patrol routes for different types of patrols requires the allocation of a certain investment. Big data management is one of the areas of specific concern. A new sphere for routing is the development of guided or automatic routes for machines that also requires the provision of funds to ensure the availability of machines, software, and professionals who can handle the needed technologies.

The Use of Drones and Robots

The lack of manpower, which is a significant challenge, can be potentially addressed with the help of such technologies as drones and robots. The idea behind patrolling is twofold as, on the one hand, police officers observe the situation in specific areas and collect data. On the other hand, the presence of police officers deters people from committing crimes or misbehaving. Drones have been employed to address these objectives, and this technology-based strategy is regarded as effective (Piciarelli & Foresti, 2020). In many cases, drones are guided by a single human operator, which has quite a limited effect on the problem of the lack of manpower. The major value of such techniques is the possibility to reach the necessary location within a short period of time (as more time is usually needed for police officers).

At present, more technologically advanced systems are making their way to routine use in law enforcement. Drone swarms can be an efficient alternative to police officers’ patrols (Piciarelli & Foresti, 2020). Such systems have already been introduced, but they are not widely utilized so far. These swarms are guided by one person (or even the corresponding software) and can cover a large territory for a substantial amount of time. One of the key attributes of such systems is the use of a comprehensive algorithm that is associated with collaboration. The drones share data, and route maps can be modified within the real-time context. This system is specifically valuable for areas with uneven coverage requirements (Piciarelli & Foresti, 2020). Clearly, these models should be enhanced by police officers’ patrolling, but reduced manpower is needed in such cases.

Learning systems and artificial intelligence are now extensively used in drone-based operations. Instead of moving in terms of the created routes, drones start developing their own routes based on real-time situations and circumstances (Piciarelli & Foresti, 2020). These gadgets move to the places that are least covered or can potentially be associated with instability. Although these systems and algorithms are not a part of daily practice in most police departments, many units have acknowledged their cost-effectiveness.

The use of robots still seems to be a part of science fiction, but they appear in different American districts and cities. Robotics has become one of the largest areas of study within the scope of law enforcement research, and numerous experiments have been conducted since the 1980s (Portugal et al., 2019). This model is also much more effective than camera-based surveillance as robots can cover larger areas and provide more data accessing more spacing and being able to send diverse types of information. The most recent topic of inquiry is now multi-robot systems that are regarded as more effective compared to single-robot alternatives.

The former creates a network of units sending different types of data to a certain data center. Based on this information, the swarm of robots or each machine can make various decisions, including the creation of optimal routes, appropriate responses to diverse situations, and so on.

As far as the issues and limitations to the use of machines in patrolling are concerned, it is possible to consider several areas. Although the use of drones is becoming increasingly widespread, battery life is a substantial problem yet to be solved. The comparatively short periods of drones’ operations set various limitations to their use, which is especially relevant when vast territories should be covered (Piciarelli & Foresti, 2020). The presence of obstacles is another issue that can hinder the effectiveness of the use of drones. Obstacles can have adverse effects on the performance of units or the communication between different devices. Finally, although drones are becoming more affordable, their purchase and maintenance require rather a considerable investment that can be scarce, especially when it comes to low-income communities.


The use of simulations has become widespread in relation to patrolling. This instrument has different applications and contributes to the development of policing practices. For instance, simulation is utilized to address the routing issue and is one of the technologies used to assess the effectiveness of patrolling models and ways to improve them (Chen et al., 2017). Simulations are employed to conduct studies aimed at improving law enforcement strategies (James et al., 2017). For instance, this technology is helpful in analyzing police officers’ behaviors and responses in diverse situations and under different conditions (James et al., 2017). Personnel’s attitudes and behavioral patterns during their response in are explored, and effective models are introduced to help police officers address certain issues.

One of the most common and effective uses of simulations is linked to law enforcement staff training. Police officers’ training is conducted with the help of digital simulations and gaming (Kent, 2020). The staff is trained to use different methods and technologies, as well as collaborate effectively. Interactions with various groups of people (offenders, victims, community members, other officers, officials, and others) are another aspect included in simulation-based training (Kent, 2020). These technological advances have proved to be valuable instruments contributing to the positive outcomes of police patrolling. Clearly, the use of this instrument still needs certain investments that can be difficult to attain in some communities. It is also seen as excessive technology less effective compared to other tools, so many departments fail to use simulations for training purposes.

Social Media

Another type of technology utilized to improve the existing patrolling practice may seem quite unrelated to the field. However, it has been acknowledged that social media can have a significant positive effect on patrolling outcomes (Wood, 2020). A meme incentive introduced by the New South Wales Police Force (Australia) in 2017 suggests that patrolling practices can be enhanced when appropriate relationships between the community and police are established.

In many settings, people are reluctant to address police officers even in cases of emergency or some risks related to public order. This reluctance is specifically common among underprivileged groups due to the lack of trust towards the police. Police brutality and negative coverage in media divert people from collaboration, which has multiple adverse effects. At the same time, by building a positive image, law enforcement professionals will be able to gain more trust and cooperation in their communities.

Social media can become an effective platform for the development of such images. Wood (2020) states that the meme strategy that encompassed sharing positive (cute and humorous) images through the police departments’ social media accounts had a positive impact on the atmosphere within the community. This strategy led to the enhanced engagement of community members, which, in its turn, had positive outcomes related to public order.

It is noteworthy that short-term effects have been identified, while long-term implications are yet to be explored. Still, such studies and initiatives show that social media can become the communication platform to bring the community and police together. Facebook, Twitter, and Instagram, as well as other networks, can become the channels to establish proper relationships and make collaboration between community members and police officers effective. Further research concerning the influence such communication has on the relations between communities and law enforcement personnel, as well as the effectiveness of policing, is needed to ensure that social media use can be successful.


To sum up, modern patrol strategies are associated with the increasing use of technology to address the most urgent challenges. Numerous digital-based models and strategies are utilized to develop and assess the effectiveness of patrol routes. Tracking systems enable law enforcement professionals to ensure that the routes are properly followed and the needed areas are covered. Communication technologies are instrumental in sharing data and facilitating the process of decision-making in real-time contexts. The technology of the future, the use of drones and robots, has become a modern reality. These units are employed effectively and enhance the safety of community members.

Clearly, further research and the development of innovative facilities and approaches are ahead. The existing advances are associated with certain limitations such as the need for considerable investment, the low capacity of some devices, errors, and the lack of skills to handle the available technologies. However, current practices and personnel’s commitment to growth and better performance are instrumental in the increasing level of technology integration into modern policing, in general, and patrol strategies, in particular.


Chen, H., Cheng, T., & Wise, S. (2017). Developing an online cooperative police patrol routing strategy. Computers, Environment and Urban Systems, 62, 19-29. Web.

Dewinter, M., Vandeviver, C., Vander Beken, T. V., & Witlox, F. (2020). Analyzing the police patrol routing problem: A review. ISPRS International Journal of Geo-Information, 9(3), 1-17. Web.

Haas, T. C., & Ferreira, S. M. (2017). Optimal patrol routes: Interdicting and pursuing rhino poachers. Police Practice and Research, 19(1), 61-82. Web.

Hutt, O. K., Bowers, K., & Johnson, S. D. (2021). The effect of GPS refresh rate on measuring police patrol in micro-places. Crime Science, 10(1), 1-14. Web.

James, L., James, S., & Vila, B. (2017). The impact of work shift and fatigue on police officer response in simulated interactions with citizens. Journal of Experimental Criminology, 14(1), 111-120. Web.

Kent, J. (2020). Use of force simulator for law enforcement handgun qualification. HCI International 2020: Communications in Computer and Information Science, 248-255. Web.

Leigh, J., Dunnett, S., & Jackson, L. (2017). Predictive police patrolling to target hotspots and cover response demand. Annals of Operations Research, 283(1-2), 395-410. Web.

Piciarelli, C., & Foresti, G. L. (2020). Drone swarm patrolling with uneven coverage requirements. IET Computer Vision, 14(7), 452-461. Web.

Portugal, D., Iocchi, L., & Farinelli, A. (2019). A ROS-based framework for simulation and benchmarking of multi-robot patrolling algorithms. In A. Koubaa (Ed.), Studies in Computational Intelligence (pp. 3-28). Springer.

Sampaio, P.A., da Silva Sousa, R., & Nazário Rocha, A. (2017). Reducing the range of perception in multi-agent patrolling strategies. Journal of Intelligent & Robotic Systems, 91(2), 219-231. Web.

Wood, M. A. (2020). Policing’s ‘meme strategy’: Understanding the rise of police social media engagement work. Current Issues in Criminal Justice, 32(1), 40-58. Web.

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